Faculty Time Expenditure Across Research, Teaching, and Service: Do Gender Differences Persist?

Abstract

Faculty members are continually confronted with a multitude of activities among which they must divide their time. Prior research suggests that while men and women academics spend the same number of weekly hours working, women tend to expend more time on teaching and service relative to men while men expend more time on research relative to women. Based on cross-sectional survey data from a sample of 783 tenured or tenure-track faculty members from multiple universities, we examine gender differences in time spent in research, teaching, and university service. Regression analyses show that gender differences in time allocation continue to persist after controlling for work and family factors. More specifically, women report more time on teaching and university service than do men, while men report more time spent on research than do women. Results provide evidence that gendered differences in faculty time allocation are robust across time. Potential implications for policy are discussed.

University faculty are expected to excel as researchers, as teachers, and as providers of service to their university. As such faculty are continually confronted with daily decisions as to how to best allocate their time. The allocation of time across various faculty activities has been a topic of research interest (Milem et al., 2000) as well as the subject of public debate (McKenna, 2018). Across faculty, research suggests that there is meaningful variation in terms of the time and effort that is allocated to different work tasks (e.g., Carrigan et al., 2011; Winslow, 2010). These differences are important as the way in which time is distributed across different activities can have implications for career outcomes such as promotion and tenure. For example, professors who had not been promoted to full professor after seven years reported spending more time on teaching and less time on research than did professors promoted in less than seven years (Link et al., 2008). Moreover, trying to meet the competing demands associated with research, teaching, and service responsibilities, as well as demands outside of work, can result in long work hours, work-family conflict, and burnout (Kreuter, 2013; Minnotte & Pedersen, 2019; Pope-Ruark, 2022). Indeed, the challenges and stresses associated with balancing the three areas of faculty work performance, along with personal life, have been well documented (e.g., Beddoes & Pawley 2014; Minnotte, 2021).

Given the known association between time allocation with career outcomes such as promotion (Link et al., 2008) and wellbeing (Dahm et al., 2015), gender differences in faculty time allocation have been a topic of particular interest (Aiston & Jung, 2015; Carrigan et al., 2011; Misra et al., 2012; Winslow, 2010). Gender has been referred to as deeply embedded in the structure of academic careers with university cultures built on ideal male worker norms that suggest faculty members should be wholly devoted to work (Minnotte, 2021; Winslow, 2010). Research indicates that while men and women work a similar number of weekly hours, women spend more time on teaching and service relative to men while men focus more time on research relative to women (e.g., Domingo et al., 2020; Winslow, 2010). These differences may be attributed to societal processes and organizational norms that assign women to tasks more highly associated with communion (i.e., teaching and service) and men to tasks more highly associated with agency (i.e., research) (e.g., Eagly et al., 2020).

However, there are limitations associated with existing research. Specifically, much of the literature is based on the National Study of Postsecondary Faculty, which was last conducted in 2004 (e.g., Winslow 2010). It may be that efforts to enhance gender equity over the past decades have diminished gender differences in time allocation. Other studies have isolated a specific activity (i.e., research, grant-writing, service) (e.g., Anderson & Slade 2016; Bentley & Kyvik, 2013; Guarino & Borden, 2017) rather than the array of research, teaching, and service activities in which faculty allocate their time. Studies that do include more detailed assessments of activities tend to be based on a single institution (e.g., Misra et al., 2011; Ziker et al., 2014).

The objective of the current study is to investigate if gender differences in faculty occupational time allocation to research, teaching, and university service persist among tenured and tenure-track faculty. To help reduce the influence of potential confounding, and to better isolate the unique effect of gender, we statistically control for work and for family factors that could serve as alternative explanations for gender differences.

In terms of work factors, we control for institutional type (i.e., research intensity) and for faculty rank. Research, teaching, and university service expectations — and the value conferred to these activities —in research intensive universities differ from universities with a less research-intensive focus (e.g., Guarino & Borden 2017; Winslow, 2010). Gender differences may be diminished or be exacerbated across these different university contexts. Research has also shown that faculty rank can impact faculty time allocation (Link et al., 2008). Service expectations tend to increase as faculty move up in rank and those with more seniority may allocate less time to activities such as teaching. In their study of faculty at the University of Massachusetts at Amherst, Misra et al. (2011) reported that gender differences in time allocation were most acute among faculty at the Associate rank. Specifically, Associate men spent seven and a half more hours a week on research than did Associate women.

Added to the occupational pressures associated with paid work time allocation, time must also be allocated to domestic activities such as dependent care. Thus, we also control for marital status and time spent on two forms of dependent care, childcare and eldercare (Winslow, 2010). Understanding time spent in unpaid domestic work such as childcare and eldercare alongside time spent in paid work activities is critical as time spent on one activity can compete with time spent in another activity, contributing to work-family conflict (Allen et al., 2020; Greenhaus & Beutell, 1985). Moreover, gender differences exist with regard to faculty nonpaid domestic work, such that women tend to spend more time on dependent care relative to men (Mason et al., 2005; Misra et al., 2012). There are some indications that family status may affect faculty time allocation (Jacobs & Winslow, 2004; Winslow, 2010).

By including recent data on research, teaching, and university service from multiple universities, we provide an updated understanding of gender differences in faculty time allocation. In sum, we aim to contribute to the existing faculty time allocation literature by providing a more nuanced assessment of gender differences in time allocation across different academic environments.

Hypothesis 1

After controlling for work and family factors, men spend more time on research than do women.

Hypothesis 2

After controlling for work and family factors, women spend more time on teaching and university service than do men.

Method

Participants and Procedure

Participants were 783 tenured or tenure-track faculty members employed at 11 public universities located across a southeastern state. Limiting the sample to tenured and tenure-track Assistant, Associate, and Full faculty was done to enhance comparability in expectations associated with research, teaching, and service. Of these, 448 (57.2%) self-identified as male and 335 (42.8%) as female. Average age was 49.46 (SD = 11.59). Participants self-identified as White/Caucasian (n = 632; 80.7%), Black/Afro-Caribbean/African American (n = 41; 5.2%), Asian/Pacific Islander (n = 47; 6%), Hispanic/Latino (n = 12; 1.5%), other (n = 42; 5.4%), and no response (n = 9). Distribution of rank was Assistant (n = 218; 27.8%), Associate (n = 282; 36%), and Full (n = 283; 36.1%). Data were collected in 2016 via an online survey administered through Qualtrics. Faculty email addresses were accessed from public University websites and through faculty listservs. Invitations to participate were sent via email. IRB approval for the study was granted by the first author’s institution.

Measures

Time allocation. Participants reported average weekly hours engaged in research, teaching, and service to the university. Examples of tasks for each category based on Misra et al. (2012) were provided to ensure participants consistently categorized tasks. Examples for research included research, reading, writing, meeting with research assistants, etc. Examples for teaching included teaching undergraduate and graduate courses, teaching preparation, grading, etc. Examples for university service included serving on committees, attending meetings, etc.

Gender. Gender was coded as man (1) or as woman (2).

Rank. Rank was coded as Assistant (1), Associate (2), or Full (3).

Institution type. We used the Carnegie Classification of Institutions of Higher Education to group universities into higher and lower research expectations institutions. Five universities were classified as R1 universities and were grouped into the higher research-intensity category (1). The other six fell into a mix of other classifications that represented less research activity and were grouped into the lower research-intensity category (2). A total of 551 participants were at higher research-intensive universities while 232 were at lower research-intensive universities.

Marital status. Participants indicated if they were single (0) or if they were living with partner/married (1). A total of 126 participants reported they were single while 599 reported they were married/partnered.

Childcare and eldercare. Participants reported average weekly hours spent on childcare and average number of hours spent on eldercare.

Results

Table 1 shows means, standard deviations, and correlations. As indicated in Table 1, bivariate correlations show that men reported more time on research (r = − .09, p < .01) than women while women reported more time on teaching (r = .10, p < .01) and on childcare (r = .11, p < .01) than men. Time spent on childcare was negatively associated with time spent on research (r = − .15, p < .01) and on teaching (r = − .15, p < .01). Unadjusted means for research, teaching, and service for men and for women are shown in Table 2. Total time spent on paid work was comparable: 59.42 h for men and 60.32 h for women. In terms of total dependent care, women spent 17.48 h on dependent care compared to 12.08 h for men (Table 2).

Table 1.

Means, Standard Deviations, and Correlations

	1	2	3	4	5	6	7	8	9
1. Gender	-
2. Rank	− 0.17**	-
3. Institution	− 0.01	− 0.17**	-
4.Marital status	− 0.19**	0.12**	− 0.08*	-
5.Childcare	0.11**	− 0.19**	0.05	0.19**	-
6. Eldercare	0.11	0.04	0.07	− 0.06	− 0.03	-
7. Research	− 0.09**	0.04	− 0.18**	− 0.04	− 0.15**	− 0.04	-
8. Teaching	0.10**	− 0.15**	0.30**	− 0.11**	− 0.15**	0.03	− 0.05	-
9. Service	0.06	0.16**	0.03	− 0.05	0.01	− 0.01	− 0.12**	0.01	-
Mean	NA	NA	NA	NA	12.92	1.48	26.21	24.09	9.51
SD	NA	NA	NA	NA	18.99	4.74	16.19	13.90	9.48

Note: *p < .05; **p < .01. Gender was coded as man (1) or woman (2). Rank was coded as Assistant (1), Associate (2), or Full (3). Institution was coded as higher research intensity (1) or lower research intensity (2). Marital status was coded as single (0) or living with partner/married (1)

Table 2.

Time Allocation Mean Hours and Standard Deviations Across Gender

Activity	Men (n = 448)	Women (n = 335)
Research	27.49 (16.39)	24.48 (15.79)
Teaching	22.94 (13.36)	25.62 (14.48)
University service	8.99 (8.74)	10.22 (10.37)
Total paid work hours	59.42	60.32
Childcare	11.05 (16.49)	15.42 (21.66)
Eldercare	1.03 (3.67)	2.06 (5.83)
Total dependent care hours	12.08 (16.79)	17.48 (22.17)

Note. Unadjusted means. Values in parentheses are standard deviations

Hierarchical multiple regression based on SPSS version 28 was used to test the hypotheses (Table 3). At Step 1 the paid work variables were entered. At Step 2 the family variables were added. Gender was added at Step 3. Dependent variables were weekly time allocated to research, to teaching, and to university service. In support of Hypothesis1, men reported allocating more time to research than did women (ß = − 0.09, p < .05). In support of Hypothesis2, women reported allocating more time to teaching (ß = 0.10, p < .01) and to service (ß = 0.08, p < .05) than did men. Findings also show that time spent on childcare was negatively associated with time spent on research (ß = − 0.12, p < .01) and on teaching (ß = − 0.21, p < .01). Eldercare was not associated with time spent on research, teaching, or university service (p > .05).

Table 3.

Regression Results

	Research	Teaching	University service
Step 1
Rank	0.01	-0.11**	0.14**
Institution type	-0.17**	0.31**	0.02
∆ R2	0.03**	0.12**	0.02**
Step 2
Rank	-0.01	-0.14**	0.17**
Institution type	-0.16**	0.31**	0.02
Childcare	-0.13**	-0.20**	0.08*
Eldercare	-0.02	0.01	-0.02
Partner status	-0.03	-0.03	-0.08*
∆ R2 Step 3	0.02**	0.04**	0.01
Rank	-0.02	-0.13*	0.18**
Institution type	-0.17**	0.32**	0.02
Childcare	-0.12**	-0.21**	0.07
Eldercare	-0.01	0.00	-0.03
Partner status	-0.05	-0.01	-0.07
Gender	-0.10*	0.09*	0.09*
∆ R2	0.01*	0.01*	0.01*
Total R2	0.06	0.17	0.04
F	7.07**	24.14**	4.55**
df	6, 718	6, 718	6, 718

Note. Standardized beta weights from each step of equation reported. *p < .05; **p < .01

∆ R² change may not sum to Total R² due to rounding error. Listwise deletion

Supplemental Analyses

To lend further insight into the data we conducted several additional analyses. First, we added whether the participant was in a STEM (science, technology, engineering, and math) versus a non-STEM discipline as an additional control. Non-STEM versus STEM categorization (non-STEM coded 1, STEM coded 2) was based on faculty self-reports of their department and on the National Science Foundation classification system (Gonzalez & Kuenzi, 2012). Due to missing data, the sample size for these analyses was reduced to 560. Results are shown in Table 4. Gender remained significant in the equation for research (ß = − 0.12, p < .01) and for university service (ß = 0.10, p < .05), but not for teaching (ß = 0.06, p = .12).

Table 4.

Regression Results with STEM vs. Non-STEM (Discipline) Added as a Control

	Research	Teaching	University service
Step 1
Rank	0.01	-0.15**	0.13**
Institution type	-0.16**	0.31**	0.01
Discipline type	0.06	-0.07	-0.09*
∆ R2	0.03**	0.15**	0.02**
Step 2
Rank	-0.00	-0.18**	0.17**
Institution type	-0.16**	0.31**	0.01
Discipline type	0.06	-0.08	-0.10*
Childcare	-0.11*	-0.23**	0.10*
Eldercare	-0.01	-0.00	-0.05
Partner status	-0.04	-0.01	-0.11*
∆ R2	0.02**	0.05**	0.02*
Step 3
Rank	-0.02	-0.18*	0.18**
Institution type	-0.17**	0.32**	0.02
Discipline type	0.04	-0.06	-0.09
Childcare	-0.10*	-0.24**	0.09
Eldercare	-0.00	-0.01	-0.06
Partner status	-0.07	0.01	-0.09*
Gender	-0.12**	0.06	0.10*
∆ R2	0.01*	0.00	0.01*
Total R2	0.06	0.20	0.05
F	5.08**	20.03**	4.20**
df	7, 553	7, 553	7, 553

Note. Standardized beta weights from each step of equation reported. *p < .05; **p < .01

∆ R² change may not sum to Total R² due to rounding error. Pairwise deletion

To further understand the importance of gender, we next conducted relative weights analyses using the Tonidandel and LeBreton (2015) online tool. RWA partitions the variance among correlated predictors, identifying the proportion of variance uniquely accounted for by each predictor (Johnson & LeBreton, 2004; Tonidandel & LeBreton, 2011; 2015). Results (see Table 5) indicate that the variable that contributed the most unique variance in research and teaching was institution type, accounting for half of the total explained variance. With regard to gender, analyses show that gender explains the second-most variance in university service (13.04%), the third-most variance in research (13.60%), and the fourth-most variance in teaching (5.79%). These values were largely consistent even after also accounting for discipline (STEM vs. non-STEM) (Table 6). Thus, while gender is not the most important predictor, it plays a nontrivial role in time allocation, particularly for research and service. Moreover, the relative weights analyses help reveal that childcare carries a greater degree of importance for research (26.14% of explained variance) and teaching (20.80% of explained variance) than does gender (13.60% and 5.79% of explained variance, respectively), but gender is more important for university service (13.04% explained variance compared to 2.53% explained variance by childcare).

Table 5.

Relative Weights Analyses

	Research	Teaching	University service
Gender	13.60	05.79	13.04
Rank	00.85	11.98	72.58
Institution type	53.16	58.41	04.20
Childcare	26.14	20.80	02.58
Eldercare	01.98	00.20	00.77
Partner status	04.27	02.83	06.82
Total R2	0.0582	0.1497	0.0425

Note. Values represent rescaled weights

Table 6.

Relative Weights Analyses with STEM vs. Non-STEM (Discipline) Included

	Research	Teaching	University service
Gender	12.33	04.68	10.28
Rank	00.80	11.20	68.05
Institution type	51.66	55.23	03.54
Childcare	26.04	19.73	02.53
Eldercare	01.82	00.15	00.88
Partner status	04.02	02.96	06.80
Discipline	03.34	06.06	07.92
Total R2	0.05900	0.1551	0.0460

Note. Values represent rescaled weights

Finally, given that some activities such as research are less discretionary within research intensive institutions, we investigated the interaction between gender and institution type.1 We included the same set of control variables used in our original analyses. Institutional type did not moderate the relationships involving research (interaction term ß = 0.13, p = .41) nor that for teaching (interaction term ß = − 0.11, p = .43). However, the interaction was significant for university service (interaction term ß = − 0.33, p = .03). The nature of the interaction was such that the relationship between gender and university service was stronger in lower research intensity institutions than in higher research intensity institutions. That is, women contributed more hours to university service across both types of institutions, but the gender difference was greater in less research-intensive institutions. The interaction effect remained significant after adding discipline type to the equation.

Discussion

Faculty positions involve multiple work role demands that often compete with one another for time (i.e., time devoted to teaching vs. time devoted to research), resulting in difficulty balancing “work-work” (Dahm et al., 2015; Misra et al., 2012). The aim of this study was to determine if faculty gender differences in time allocation across research, teaching, and university service persist. The total summed paid work hours across research, teaching, and service are virtually equal across men (59.43) and women (60.32). However, the way in which these hours are distributed continue to be gendered. Results indicate that after controlling for rank, institution type, marital status, and two forms of dependent care, men continue to report more time expended on research while women report more time expended on teaching and on university service. When further controlling for type of discipline on the reduced sample, gender differences remained for research and for university service. Our findings also indicate that gender differences in university service are exacerbated in lower research intensity university settings. These findings have implications for gender differences in faculty wellbeing in that Dahm et al. (2015) reported that time spent on research is positively associated with work satisfaction and psychological wellbeing while time spent on teaching and service is negatively associated with work satisfaction and psychological wellbeing.

Results also demonstrated that time spent on childcare is negatively associated with research and with teaching. This is important in that women report engaging in total dependent care 5.4 more hours a week than men, which sums to a total of 280.8 h a year. Moreover, the supplemental relative weights analyses indicated that time spent on childcare was the second most important predictor of time spent on research and on teaching. The strong relationship between childcare and time spent on research and on teaching are noteworthy. The challenges associated with managing work and family roles, particularly parenting, are well recognized among faculty, with parenting referred to as a threat to the ideal worker norm (Beddoes & Pawley, 2014; Drago et al., 2006; Goulden et al., 2011; Morgan et al., 2021). Understanding the tradeoffs faculty make in time allocation decisions is important given the implications for career success and for wellbeing (Bozeman & Gaughan, 2011). However, we also note that given gender remains significant after controlling for dependent care, addressing gendered caregiving inequities is likely to reduce, but not eliminate gender differences in research and teaching time allocation.

Implications

Our findings have key implications for occupational health and wellbeing. As the results of the current study suggests, the nature of academic reward systems coupled with high control, flexible work lends itself to long faculty work hours (Minnotte, 2021). Extensive time spent engaged in work activities suggests that faculty may have little time to psychologically or physically disengage from work, a key element necessary for recovery (Sonnentag, 2012; Sonnentag et al., 2017). Faculty referrals to university mental health services rose by 64% between 2009 and 2015 (Morrish, 2019). Moreover, because our data were collected prior to the COVID-19 pandemic, it is likely that faculty vulnerabilities to long hours and blurred boundaries have become further heightened (Kossek et al., 2021; Myers et al., 2020). Indeed, the topic of faculty burnout due to crushing workloads has received considerable attention over the past several years and has been identified as a growing problem (e.g., Malisec, 2022; McMurtrie 2020; Pope-Ruark, 2022).

Although time allocation has a discretionary component, faculty are constrained by institutional expectations and norms (Winslow, 2010). Thus, institutional policies that accommodate faculty caregiving responsibilities are needed (Shollen et al., 2009). To date, institutional strategies to acknowledge and support the caregiving activities of faculty have typically been insufficient and in some cases counterproductive (e.g., Ledgerwood et al., 2021). To effectively dismantle masculine ideal worker norms, structural changes that consider both policy and culture will be required (Sallee, 2012). For example, in addition to providing parental leave time, organizations should consider the general tempo and tenor of academic life such as not holding meetings during times that conflict with caregiving, flexible teaching schedules, and normalizing the behavior of all faculty who take time off for caregiving. Programs such as the Career-Life Balance initiative by the National Science Foundation, which provides supplements to support caregiving, are a good example of how the caregiving responsibilities of faculty can be supported.

In addition, the gender differences in time allocation we observed may have become further exacerbated over the last several years. For example, women in STEM reported loss of research time and a 40% decrease in research productivity compared to men pre and post pandemic (Myers et al., 2020). These differences have been attributed to increased caregiving responsibilities due to school and childcare closures (Myers et al., 2020). The pandemic further exposed the deeply rooted obstacles faced by women faculty associated with caregiving obligations, jeopardizing prior investments made to address the problem of gender inequities (Helman et al., 2020; Ledgerwood et al., 2021).

Limitations

Several limitations associated with the current study should be acknowledged. One is that our data are cross-sectional and thus we cannot draw causal conclusions. However, given our focus on gender differences, this is less of a concern as time spent on research, teaching, and service is not likely to predict one’s gender identity. Another limitation is that we assessed gender as a binary variable. In future studies examining the role of gender and time allocation, research is needed that is more inclusive of gender fluid/non-binary identities. Another limitation is that our data were based on self-report, which can be vulnerable to responses biases. The lack of fixed schedules associated with academic work may lend itself to inaccuracies in self-reports. However, our pattern of results with regard to the direction of gender differences exhibit similarities to previous studies lending support to their reliability. One could also argue that the small amount of variance in research, teaching, and service accounted for by gender beyond our control variables (1%) is negligible and may not persist with further control variables added to the equation (such as was the case with teaching when discipline type was controlled). However, the gender differences in actual time allocation as shown in Table 2 underscore how such differences can add up to meaningful time discrepancies across time. For example, men report 3.01 more hours a week (5%) spent on research than do women. Across a 52-week year that difference sums to 156.52 h a year (almost a month of dedicated research work), a substantial difference that could certainly have productivity implications. Finally, our participants were drawn from public universities within a particular region within the U.S. We cannot be certain the extent the results generalize across faculty.

Future Research

Consistent with prior faculty time allocation studies, our approach is descriptive. Future research is needed to better understand why gender differences continue to persist, including a better understanding of top-down pressures that dictate time allocation. Additional research on broad societal and structural interventions and practices that support equitable work in both work and home domains is also needed. In the workplace, this may include formally rewarding teaching and mentorship at university and professional levels and/or equitably distributing service (Bergman, 2019; O’Meara et al., 2018). O’Meara et al. (2018) recently developed and tested an intervention intended to enhance faculty workload equity. The intervention included information on how implicit bias can shape faculty workload allocation, how to create a work activity dashboard that provides transparency on faculty work activities, and shared information on policies and practices that can facilitate equitable workloads (e.g., rotation policies for time intensive roles). Faculty in the intervention condition were more likely than faculty in the control condition to report practices that supported equity and perceived fairness in teaching and service work. We also suggest greater research into how university practices and culture contribute to the expectation of long work hours. University administration can establish norms for working hours. For example, faculty can be discouraged from checking and responding to email 24/7. Standard policies could be set with regard to expectations associated with responsivity to student emails (e.g., within 48 h versus within 24).

Investigating the self-regulatory and perceptual properties of research, teaching, and service is needed to understand time allocation patterns more fully. Based on previous scholarship, teaching and service are perceived to have greater task closure and more prosocial aspects relative to research, which is thought to involve more complexity and delayed gratification (Dahm et al., 2015). Examining how role partners perceive different responsibilities and how time is negotiated with others could yield further insights into faculty time allocation across tasks. For example, partners at home may understand the need to take an evening to prepare for next day classroom teaching but view research as a more individual discretionary activity that is not necessary for evening work. Research on Covid-related effects may support that conclusion, as women scientists with young children reported their research time was significantly reduced by the effects of the pandemic (Myers et al., 2020).

Future research is also needed that takes an intersectional approach to examination of faculty time allocation. Despite our relatively large sample size, the majority of our participants were White, precluding our ability to analyze gender differences within historically underrepresented faculty. Women of color in particular may feel compelled to adhere to ideal worker norms in order to “fit in” (Kachchaf et al., 2015; Turner, 2002).

Conclusion

We provide a comprehensive examination of gender differences in faculty time allocation to research, teaching and university service, controlling for work and family variables. Our results from data that consider the academic array of activities across multiple universities align with those of past research, indicating that gendered patterns of time allocation are robust across time. In addition to gender, we also find that on the work side, institution type is a key contributor to time spent on research and teaching and that rank is a key contributor to time spent on university service. On the family side, we find that time spent on childcare play a significant role in time spent on research and teaching. Given long faculty work hours, further investigation into faculty time allocation seems warranted.

Authors’ Contribution

All authors contributed to study conception and design.

Funding

This research was supported by the National Science Foundation under Grant #1461617.

Data Availability

Data can be made available upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Institutional Review Board at the University of South Florida. Informed consent was obtained from all individual participants in the study.

Consent for publication

Not applicable. No individual data is identified.

Competing interests

The authors have no conflicts of interest to report.